CVE-2025-40904

A Stored HTML Injection vulnerability was discovered in the Smart Polling functionality due to improper validation of an input parameter. An authenticated user with limited privileges can push malicious remote strategies containing HTML tags through the sync. When a victim views the affected remo...

Steering LLM Viewpoints through Fabricated Evidence Injection

As chatbots increasingly influence daily decision-making, their potential to produce misleading responses poses substantial risks to users. This paper investigates a critical cognitive vulnerability in LLMs: their tendency to uncritically trust external context when presented with fabricated...

Credential Disclosure in (EU) Digital Identity Wallets: Privacy Risks and Practical Mitigations

The European Union will introduce the EUDI Wallet by late 2026, which allows users to hold digital credentials i.e., representations of physical official identity documents on their devices. This will allow users to securely and privately disclose identity attributes to websites. Although such a...

TeleHunt: A Framework and Tool for Efficient Cybercriminal Community Discovery on Telegram

This paper presents TeleHunt, a framework and tool for evaluating the effectiveness of different strategies to discover cybercriminal communities on Telegram. TeleHunt employs a set of reference-driven snowballing strategies, integrating message-level classification, contextual filtering, and...

Description-Code Inconsistency in Real-World MCP Servers: Measurement, Detection, and Security Implications

The Model Context Protocol MCP has emerged as a critical standard empowering Large Language Models LLMs to utilize external tools. In this ecosystem, LLMs rely on natural language descriptions provided by MCP servers to select and execute functions. This interaction implicitly assumes that tool...

Quality-Diversity Evolution for Discovering Diverse Vulnerabilities in LLM Safety

Current approaches to LLM adversarial testing suffer from coverage gaps: manual red-teaming does not scale, LLM-as-attacker methods exhibit mode collapse, and gradient-based approaches produce uninterpretable gibberish. We introduce a quality-diversity evolutionary framework that operates at the...

R+R: Reassessing Java Security API Misuse in Current LLMs: A Replication on JCA and JSSE APIs with External Security Knowledge

The misuse of Java security APIs is a serious security problem in software development. Research in 2024 has shown that this problem is widespread in LLM-generated code. However, it remains unclear whether this phenomenon persists in current models and how external security knowledge affects it...

An Empirical Evaluation of LLM-Generated Code Security across Prompting Methods

The growing use of Large Language Models LLMs for automated code generation has enhanced software development efficiency, but often at the cost of security. Generated code frequently overlooks critical concerns, leaving it vulnerable to issues such as weak encryption and improper input validation...

From Preventive to Reactive: How AI Coding Assistants Transform Developers' Security Awareness

AI coding assistants are now central to professional software development, yet their impact on how developers think about and practice security remains poorly understood. While prior work has documented vulnerability rates in AI-generated code, a more fundamental question persists: how do these...

CVE-2025-40904

A Stored HTML Injection vulnerability was discovered in the Smart Polling functionality due to improper validation of an input parameter. An authenticated user with limited privileges can push malicious remote strategies containing HTML tags through the sync. When a victim views the affected remo...

CVE-2025-40904 HTML injection in Smart Polling in Guardian/CMC before 26.1.0

A Stored HTML Injection vulnerability was discovered in the Smart Polling functionality due to improper validation of an input parameter. An authenticated user with limited privileges can push malicious remote strategies containing HTML tags through the sync. When a victim views the affected remo...

CVE-2025-40904

A Stored HTML Injection vulnerability was discovered in the Smart Polling functionality due to improper validation of an input parameter. An authenticated user with limited privileges can push malicious remote strategies containing HTML tags through the sync. When a victim views the affected remo...

HTML injection in Smart Polling in Guardian/CMC before 26.1.0

Summary A Stored HTML Injection vulnerability was discovered in the Smart Polling functionality due to improper validation of an input parameter. Impact An authenticated user with limited privileges can push malicious remote strategies containing HTML tags through the sync. When a victim views th...

Security Analysis of a Communication Protocol: MQTT

This paper analyzes the security of the Message Queuing Telemetry Transport MQTT protocol in the context of the Internet of Things IoT. The main objective consists of identifying vulnerabilities and proposing security improvements. Adopting a hybrid methodology, a theoretical review was combined...

Context-Aware Spear Phishing: Generative AI-Enabled Attacks against Individuals Via Public Social Media Data

We demonstrate how publicly available social-media data and generative AI GenAI can be misused to automate and scale highly personalized, context-aware spear-phishing campaigns. With minimal attacker effort, a small amount of public activity per target is sufficient for GenAI models to extract...

Threat Modelling Using Domain-Adapted Language Models: Empirical Evaluation and Insights

Large Language ModelsLLMs are increasingly explored for cybersecurity applications such as vulnerability detection. In the domain of threat modelling, prior work has primarily evaluated a number of general-purpose Large Language Models under limited prompting settings. In this study, we extend th...

Security Risks in Tool-Enabled AI Agents: A Systematic Analysis of Privileged Execution Environments

Tool-enabled AI agents are increasingly deployed in cloud-hosted environments and offered as services, where they perform side-effecting operations through privileged tools within execution environments. While such agents enable powerful automation, the security implications of hosting autonomous...

AI-Accelerated Brute Force Cryptanalysis

Modern cryptography is hinged on "not learning from mistakes": trying numerous wrong keys, should not help one identify the right key. Indeed, it worked -- until recently when the surprising power of AI to see pattern in apparent randomness has turned the 'wrong plaintexts' generated by the 'wron...

On Fixing Insecure AI-Generated Code through Model Fine-Tuning and Prompting Strategies

The security of AI-generated code remains a major obstacle to its widespread adoption. Although code generation models achieve strong performance on functional benchmarks, their outputs frequently contain bugs and security weaknesses that undermine their trustworthiness. Prior work has explored a...

Security Attack and Defense Strategies for Autonomous Agent Frameworks: A Layered Review with OpenClaw As a Case Study

Autonomous agent frameworks built upon large language models LLMs are evolving into complex, tool-integrated, and continuously operating systems, introducing security risks beyond traditional prompt-level vulnerabilities. As this paradigm is still at an early stage of development, a timely and...